Introduction to R

The History

Mayank Agrawal
Senior R developer Consultant I
ProCogia

Thursday, August 17, 2023

R is Quirky

“The best thing about R is that it was written by statisticians. The worst thing about R is that it was written by statisticians.” - Bow Cowgill, Google

Hello, There

This presentation will touch base on the following sections:

  • Introduction
  • Interesting Facts about R
  • Why use R?
  • RStudio IDE
  • R vs Python
  • The R Ecosystem
  • R Popularity Ranking

Introduction

  • R is primarily a statistical language developed in 1993-1995 by Robert Gentleman and Ross Ihaka at the University of Auckland, Auckland, New Zealand.
  • Over the years, R has matured to be one of the preferred languages in the coding arsenal of Statisticians, Data Scientists, Data Engineers, Data Analysts and Data Miners.
  • Application Domains: Healthcare, Academics, Consulting, Finance, Insurance, Media, and many more.
  • Most famous applicability trend: Machine Learning, Data/Business Analytics, Data Visualization, Dashboard Development, and Analytics Application Development.
  • R is available across platforms - Windows, Linux, MacOS.

Interesting Facts about R

  • R is open-source programming language with its roots from S programming language.
  • R was conceived in 1993, initial version was released in 1995 and a stable R version was released in 2000.
  • It was named after the first names of its first two authors.
  • A hidden gem, R supports both procedural programming and object-oriented programming.
  • The number of R packages available either through CRAN or GitHub is 1, 00, 000 and they do epic stuff with just one line of code. It could range from Regression to Bayesian analysis.
  • Started gaining popularity for its support for reproducible workflow from researchers at academia.

Why use R?

  • 878 R User groups, 90 countries, 414 cities, 775,379 members.
  • Open-Source programming language.
  • Rich eco-system to help end-to-end analytics flow from data sourcing, data loading, data manipulation, data engineering, analytics, dashboard development, report renders, automated emails to schedulers.
  • Ability to integrate with other programming languages - Python, Java, .Net, C, C++ and much more.
  • Has one of the strongest vast active community of R users, growing day-by-day.
  • Multiple micro communities to share learnings - R Ladies, R Consortium, R Stats, R Weekly, R Users, Data Science Hangout,
  • Backed by POSIT ongoing innovation and focus on ease of use and expanding capabilities.
  • Check out R User Community Dashboard

RStudio IDE

RStudio IDE Continued

  • RStudio is the preferred IDE (Integrated Development Environment) for R programming.
  • RStudio is free and open source.
  • USP: version control and project management.
  • RStudio has four main panes each in a quadrant of your screen:
    • Source Editor
    • Console
    • Work space Browser (and History), and
    • Plots (and Files, Packages, Help).

R Products Integrations

R Ecosystem

R Popularity Ranking (Dec 2022)

R Vs Python

Feature R Python
Scope Statistical language General purpose language
First Release 1993 1991
USP Statistical analysis, data exploration and visualization ML, Deep Learning, Big Data
IDE R Studio, VSCode Jupyter notebooks, Spyder, VSCode, PyCharm
Common Libraries tidyverse, caret, shiny, rmarkdown, ggplot2, plotly Pandas, Numpy, Matplotlib, TensorFlow, scikit-learn
Eco System ~20,000+ packages on CRAN ~300,000+ packages on PyPi
Trend (Dec 2022) 11 in TIOBE and 7th in PYPL 1 in TIOBE and 1 in PYPL

References

  • The R Ecosystem Slides Link
  • R: Then Vs Now Slides Link
  • R popularity index Link
  • R Programming Introduction Link
  • R Community Shiny Dashboard Link
  • R User Community Shiny Dashboard Link
  • R Ladies Shiny Dashboard Link